What are the hardware requirements for Mergekit Slerp Mirtnuv?

Mergekit Slerp Mirtnuv requires approximately 24.5 GB of VRAM and supports a context window of 1000K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mergekit Slerp Mirtnuv and how large is it?

Mergekit Slerp Mirtnuv is developed by mergekit-community, a model with 12b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Mergekit Slerp Mirtnuv?

Mergekit Slerp Mirtnuv is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mergekit Slerp Mirtnuv by mergekit-community — VRAM 24.5GB, 1000K context

Name: Mergekit Slerp Mirtnuv
Author: mergekit-community

Mergekit Slerp Mirtnuv is an open-source language model by mergekit-community. Features: 12b LLM, VRAM: 24.5GB, Context: 1000K, Merged, LLM Explorer Score: 0.17.

Merged Model Base model:redrix/matricide-12... Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mergekit-community/mergekit-slerp-mirtnuv

Mergekit Slerp Mirtnuv Parameters and Internals

LLM Name	Mergekit Slerp Mirtnuv
Repository 🤗	https://huggingface.co/mergekit-community/mergekit-slerp-mirtnuv
Base Model(s)	...ricide 12B Unslop Unleashed V2 Mergekit Slerp Ljgqjtg redrix/matricide-12B-Unslop-Unleashed-v2 mergekit-community/mergekit-slerp-ljgqjtg
Merged Model	Yes
Model Size	12b
Required VRAM	24.5 GB
Updated	2026-07-24
Maintainer	mergekit-community
Model Type	mistral
Model Files	4.9 GB: 1-of-5 4.9 GB: 2-of-5 4.9 GB: 3-of-5 4.9 GB: 4-of-5 4.9 GB: 5-of-5
Model Architecture	MistralForCausalLM
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.48.2
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the Mergekit Slerp Mirtnuv capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Mergekit Slerp Mirtnuv

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...r Nemo 12B Instruct R 21 09 24	1000K / 24.5 GB	396277	141
MN 12B Mag Mell R1	1000K / 24.5 GB	69558	238
Riverfish Rocinante 12B SFT	1000K / 49.4 GB	166	1
Riverfish Rocinante 12B	1000K / 49.4 GB	111	1
MN 12B LucidFaun RP RU	1000K / 24.5 GB	1005	6
Qliphoth 12B V1.2	1000K / 24.5 GB	107	7
Captain Eris BMO Violent 12B	1000K / 24.5 GB	305	2
Shining Gold Sakura 12B	1000K / 24.5 GB	52	2
Dans SakuraKaze V1.0.0 12B	1000K / 24.5 GB	7	21
...n Eris BMO Violent GRPO V0.420	1000K / 24.5 GB	92	3

Note: green Score (e.g. "73.2") means that the model is better than mergekit-community/mergekit-slerp-mirtnuv.